16.10
Meteorological and photochemical modeling of ozone and carbon monoxide episodes for the Paso del Nortre Airshed. Part I: Mesoscale modeling.
Randolph J. Evans, ENSCO, Inc., Melbourne, FL; and M. K. Atchison, M. E. Capuano, C. A. Emery, M. A. Yocke, K. Costigan, C. Tremback, J. W. Yarbrough, R. Karp, and V. H. P. Figuero
The purpose of the analysis was to model episodes of carbon monoxide and ozone exceedences in the Paso del Nortre Airshed of El Paso, TX and Juarez, Mexico. The RAMS mesoscale model was used to produce three-dimensional meteorological fields that were used as input to the CAMx model. RAMS is a three-dimensional, multiple nested grid prognostic mesoscale model. CAMx is a three-dimensional photochemical grid model designed to calculate the concentrations of both inert and chemically reactive pollutants by simulating the physical and chemical processes in the atmosphere. The Paso del Nortre Airshed is located in region characterized by rough terrain. North Franklin Mountain (elev. 2192 m msl), is located approximately 15 km north of El Paso (elev. 1147 m msl). The soil characteristics and rough terrain significantly affected the RAMS modeling because of the strong surface and terrain forcing of the meteorological processes. For this modeling exercise we tried many different modeling configurations before we obtained RAMS data which was useful for CAMx.
For this project, we configured RAMS with 4 nested grids and a finest horizontal grid spacing of 1 and 2 km. Data used for the initialization and boundary conditions were NCAR/NCEP Reanalysis gridded 2.5-degree data along with standard surface and upper air observational data provided at 12 hour intervals for the 3-4 day simulations. Additional air monitoring meteorological sites provided data for verification of the model.
This paper discusses the mesoscale modeling effort, the problems encountered, and provides insight into configuring a mesoscale forecast model for use as a data provider to a regional photochemical grid model. Model results and comparisons with surface observations, rawinsondes, and acoustic sounder data are presented. The photochemical modeling using CAMx is described in a companion paper.
Session 16, Meteorological analysis and forecasting of ozone episodes: Continued (Parallel with Session 17)
Thursday, 13 January 2000, 1:30 PM-3:15 PM
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